Towards ‘augmented sociology’? A practice-oriented framework for using large language model-powered chatbots

Abstract

Artificial intelligence (AI) chatbots powered by large language models (LLMs) such as ChatGPT are rapidly gaining popularity as labour-augmenting tools. This paper is for sociologists seeking to make the best use of this technology in their work. It presents a practice-oriented framework for using AI chatbots in sociology, building on considerations of the technical conditions of LLMs to introduce both a task categorization and the concept of a ‘knowledge funnel’. This model illustrates the relationship between the scope of knowledge and accuracy in outputs to guide sociologists in evaluating the reliability and applicability of AI-generated content in their research. The main argument driving this article is to establish a paradigm of ‘augmented sociology’ that focuses on human–AI interaction and understands LLMs as a resource rather than as a replacement. This augmentation manifests itself clearly in dialogic ideation, enhancing research by bridging domains, and broad methodological assistance. The paper's primary contribution lies in introducing specific terminologies and actionable strategies for sociologists to integrate LLM chatbots creatively and effectively in their work, filling a significant gap in the current academic understanding of generative AI's role in sociology.